Triple
T9964377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alto Alentejo |
E195643
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Marvão |
E549127
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Marvão | Statement: [Alto Alentejo, hasTown, Marvão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marvão Context triple: [Alto Alentejo, hasTown, Marvão]
-
A.
Marvão
chosen
Marvão is a fortified medieval village in Portugal known for its hilltop castle and panoramic views over the Alentejo region.
-
B.
Portalegre
Portalegre is a historic city in eastern Portugal known for its medieval architecture, hilltop setting near the São Mamede mountains, and traditional Alentejo culture.
-
C.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
D.
Mosteiros
Mosteiros is a coastal municipality on the island of Fogo in Cape Verde, known for its volcanic landscapes, coffee production, and black-sand beaches.
-
E.
Mosteiros
Mosteiros is a coastal civil parish on the western tip of São Miguel Island in the Azores, known for its volcanic rock formations, natural swimming pools, and scenic Atlantic views.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71a33b48190a18c1a9023f249d2 |
completed | April 2, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e531dfa48190b57fcd2444de1ab7 |
completed | April 5, 2026, 10:41 p.m. |
Created at: March 30, 2026, 8:47 p.m.